CodeSLAM

CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM

Abstract

While each keyframe with a code can
produce a depth map, the code can be optimised efficiently jointly with pose variables and together with the codes of overlapping keyframes to attain global consistency
对关键帧进行编码,跟姿态和重叠的关键帧一起优化

contributions

  • The derivation of a compact and optimisable representation of dense geometry by conditioning a depth autoencoder on intensity images.
  • The implementation of the first real-time targeted
    monocular system that achieves such a tight joint optimisation of motion and dense geometry

个人理解

  • 使用光度信息进行code的自动编码,用RGB-D数据进行训练,然后得到每个code的深度,属于直接法的一种
  • SLAM系统:利用滑动窗口的方式,重建利用了SFM
最后编辑于
©著作权归作者所有,转载或内容合作请联系作者
平台声明:文章内容(如有图片或视频亦包括在内)由作者上传并发布,文章内容仅代表作者本人观点,简书系信息发布平台,仅提供信息存储服务。

推荐阅读更多精彩内容